An integrated inventory of One Health tools: Mapping and analysis of globally available tools to advance One Health
Notice bibliographique
Résumé
Abstract The global demand from multi-sectoral partners for operational tools for One Health implementation and capacity building is increasing, yet a validated global inventory of One Health tools did not exist. Here, we map and analyze available One Health tools and assess their suitability to support One Health implementation, including the One Health Joint Plan of Action 2022–2026 (OH JPA). Our objectives were to identify (i) publicly available One Health tools to support capacity building and OH JPA implementation; (ii) optimal outcomes for countries/regions using available One Health tools; (iii) linkages to OH JPA Action Tracks and pathways in the One Health Theory of Change (TOC); and (iv) gaps and priorities for the development of additional One Health tools. One Health High Level Expert Panel (OHHLEP) members compiled information on One Health tools that were publicly available and released up to June 30, 2023, via online sources and partner networks including the Quadripartite organizations. Inclusion criteria addressed One Health relevance, use at the national, subnational, or regional level in ≥5 locations, and publicly available information. Tools were assessed for applicability by OH JPA action track, TOC pathway, scope, and intended outcomes, as well as the extent to which tools addressed gender equality, social inclusion, and environmental dimensions of One Health. Of 132 candidate tools, 50 (38%) met the inclusion criteria. These tools addressed all six OH JPA Action Tracks, but relatively fewer tools addressed Action Tracks 4 (Food Safety), 5 (Antimicrobial Resistance), and 6 (Environmental Integration). Tools were available to support all three TOC outcome pathways, and many addressed more than one Action Track and TOC outcome pathway. Most available One Health tools addressed assessment and to a lesser extent implementation, with fewer tools available for action planning, prioritization, and monitoring. Gaps and opportunities for improving One Health tools were identified, including the integration of the environment dimension, gender equality, and social inclusion. Ultimately, our findings will contribute to further the advancement of One Health globally, including via OH JPA implementation, while spurring adjustments to existing One Health tools and the development of new ones to address key gaps. One Health impact statement The One Health approach is gaining momentum globally, and this study represents the first integrated mapping and analysis of globally available One Health tools. Our findings aim to improve the quality, applicability, and availability of tools to support One Health implementation at the subnational, national, regional, and global levels, including through the Quadripartite’s One Health Joint Plan of Action. By using the OHHLEP definition of One Health to assess available One Health tools and map them onto the One Health Joint Plan of Action, we identify the need for a systematic approach and enhanced integration across dimensions of One Health to lead to sustainable One Health systems.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,039 | 0,092 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,034 | 0,055 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,007 | 0,007 |
| Science ouverte | 0,002 | 0,008 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».